Senior Environmental Data Scientist

Role Description

We are hiring a Senior Environmental Data Scientist to lead the technical development of nature and biodiversity data solutions. This is a high-impact individual contributor role for an environmental scientist first and foremost who is additionally an accomplished data scientist and programmer.

You’ll be responsible for transforming scientific research into scalable analytics, building robust environmental data products, and supporting product development through direct technical contribution. You will also play a soft leadership role — supporting and mentoring junior data scientists, guiding generalists on environmental matters, and helping shape the long-term data science capacity of the Nature & Biodiversity team.

This is a senior-level hire with a clear path to team leadership as our company grows. You will report to the Head of Nature & Biodiversity Products .

Job Duties And Responsibilities

• Lead Development of Data Solutions: Design and implement advanced data pipelines, metrics, and models that assess how businesses interface with nature.
• Apply Environmental Science at Scale: Translate robust environmental science into analytical workflows that can support business decisions and regulatory needs.
• Drive Methodological Rigor: Incorporate peer-reviewed methodologies and scientific best practices into product development; stay ahead of innovations in the field.
• Architect Scalable Data Solutions: Develop performant, production-ready code and collaborate with engineers to build tools for spatial, temporal, and exploratory analysis.
• Mentor and Guide: Support junior data scientists, serve as the go-to environmental expert across functions, and help build the team’s overall environmental data science capacity.
• Engage with Frameworks: Apply knowledge of sustainability disclosure and risk frameworks (e.g. TNFD, ESRS, SBTN, SFDR) to develop solutions that meet evolving stakeholder needs.
• Collaborate and Communicate: Work cross-functionally with product, research, and engineering teams to translate scientific insight into real-world impact. Represent your work with external stakeholders as needed.
  
  

Requirements Experience, Qualifications And Skills

• Environmental Expertise: PhD (preferred) or Master’s in environmental science, ecology, conservation, geosciences, or a closely related field.
• Experience: 5+ years applying data science to environmental or sustainability contexts; experience in a product-oriented or startup environment is a must.
• Programming & Engineering: Expert Python developer with strong engineering discipline (e.g., Git, unit testing, CI/CD); experience building high-quality analytical code.
• Geospatial & Remote Sensing: Advanced skills in spatial analysis, GIS tools, and remote sensing data workflows (e.g., raster/vector processing, spatial joins, indexing).
• Data Science & Machine Learning: Proficiency in statistical modelling, spatial ML, and fundamental AI/ML methods (e.g., scikit-learn, PyTorch, foundation models).
• Data Systems: Hands-on experience with relational and spatial databases (e.g., PostGIS), cloud data tools (e.g., Snowflake), and handling unstructured and structured data.
• Framework Fluency: Demonstrated ability to interpret and implement solutions aligned with environmental frameworks such as TNFD, ESRS, SFDR, and SBTN.
• Communication: Ability to explain complex ideas clearly to both technical and non-technical audiences; experience with data storytelling and visualization is a plus.
• Team Fit: Collaborative, proactive, impact-driven, and adaptable — comfortable with the fast pace and opportunities of a growing startup.
  
  

Preferred Qualifications

• Deep experience with one or more particular nature-related domains, such as: biodiversity impact modeling; physical risk analysis; nature risk valuation.
• Experience contributing to or leading cross-disciplinary scientific or open-source projects.
• Work experience at corporate sustainability offices, financial institutions, regulatory bodies, or nature data providers.